2.4:
Relative Frequency Distribution
Consider a frequency distribution table with different heights listed in the first column and the number of hockey players for each class listed in the second column.
The sum of the frequency values represents the total number of players in the sample.
A relative frequency distribution gives the ratio of the number of players under each class to the total number of players.
For example, for the first class, dividing the frequency by the sum of all the frequencies gives the relative frequency of 0.05.
Similarly, the relative frequencies for each class are calculated and listed in the third column. Note that the sum of all relative frequencies must be close to one. Relative frequency is helpful to identify how common the value is in the data set.
2.4:
Relative Frequency Distribution
A relative frequency distribution is the proportion or fraction of times a value occurs in a data set. To find the relative frequencies, one can divide each frequency by the total number of data points in the sample. It is very similar to a regular frequency distribution, except that instead of reporting how many data values fall in a class, a relative frequency distribution reports the fraction of data values that fall in a class. These fractions or proportions are called relative frequencies and can be given as fractions, decimals, or percents.
Admittedly, there is not much difference in constructing a relative frequency distribution from constructing a regular frequency distribution. The starting process is the same, and the same guidelines must be used when creating classes for the data. The only key difference between a frequency distribution graph and a relative frequency distribution graph is that the vertical (y-axis) axis uses proportional or relative frequency rather than simple frequency.
Relative frequency distributions are often displayed in frequency polygons and in histograms.